HYBRID CLOUD INTEGRATION

Enable Real-Time Integration from On-Premises to Cloud and Back

CONTINUOUS DATA MOVEMENT AND PROCESSING FOR HYBRID CLOUD

While cloud environments bring agility and cost savings, working in hybrid cloud and multi-cloud environments creates new data siloes for IT teams to overcome. Striim enables fully-connected hybrid cloud environments via continuous real-time data movement and processing across on-prem data sources and a wide variety of cloud services on Microsoft Azure, AWS and Google Cloud platforms. With in-memory stream processing, Striim allows you to store only the data you need in the format you need.

Offload operational workloads to cloud by moving data in real time and in the desired format

Easily adopt a multi-cloud architecture by seamlessly moving data across different cloud service providers: Azure, AWS, and Google Cloud

Filter, aggregate, transform, and enrich your data-in-motion before delivering to the cloud in order to optimize cloud storage

Migrate your data to the cloud without interrupting business operations

Striim delivers real-time data to Microsoft Azure, Amazon, and Google Cloud. It can run on-premises or in Azure,AWS, and/or Google Cloud as a subscription-based service allowing a flexible data management architecture.

A EUROPEAN COURIER EXPRESS PARCEL COMPANY

This leading courier company in Europe embarked on its cloud journey with the help of Striim. The company is moving its data warehousing and analytics solutions to the cloud, and uses Striim to move real-time data from transactional systems running on Oracle databases to Google BigQuery to enable cloud-based analytics. Google BigQuery serves as the operational data store supporting real-time reporting and ad-hoc queries. The company plans to use real-time transactional data for fleet optimization and real-time shipment status notifications to customers.

Moved the operational data store (ODS) to the cloud by ensuring up-to-date transactional data is available in the cloud

Eliminated the performance impact of running ad-hoc queries on the production OLTP systems